POS0506 DIFFERENT BIOACTIVE LIPID PROFILES PREDICT RESPONSE TO TNF OR IL6 INHIBITORS IN RHEUMATOID ARTHRITIS: RESULT OF THE CorEvitas CERTAIN COMPARATIVE EFFECTIVENESS STUDY
Authors: M. Alotaibi, R. Coras, D. A. Pappas, J. M. Kremer, G. Thiele, T. Mikuls, M. Jain, M. Guma
Journal: Annals of the Rheumatic Diseases (2022)

Background Circulating bioactive lipids can provide information about the pathogenesis of specific diseases and potentially help predict therapeutic response. Choosing the right biological therapy earlier in the course of rheumatoid arthritis (RA) could help reach the goal of remission. Objectives We hypothesized that circulating bioactive lipids at baseline would identify specific metabolic profiles that predict patient response to therapy and define elements of metabolic pathobiology in arthritis. Methods Bioactive lipids were measured in plasma from two cohorts of RA patients from the CorEvitas (formerly known as Corrona) CERTAIN registry (1) at baseline prior to treatment with TNF inhibitors (all biologic naïve, N=102) or anti-IL6 (all previously exposed to biologics, N=114). Response to treatment was categorized by minimal clinically important difference (MCID) in Clinical Disease Activity Index (CDAI) (2) at 6 months after treatment initiation. Patients had to have a 6 month follow up visit and plasma available at both the baseline and the f/u time points. Liquid chromatography (LC) system coupled with high resolution QExactive orbitrap mass spectrometer (LC/MS) was used for bioactive lipids profiling. Around 300 spectral features were identified as potential oxylipins by searching against an in-house MS/MS library. Logistic regression analyses adjusted for gender, age and BMI was perfomed using R software. Results 102 patients (average age 54, standard deviation [SD] 12.6, 82% female [83], average BMI 29.7, SD 6.7, average CDAI 27.1, SD 13.7) starting anti-TNF therapy and 114 patients (average age 57, SD 13, 90% female [102], average BMI 30.5, SD 7.4, average CDAI 28.7, SD 13.8) starting tocilizumab were analyzed. Twenty-five bioactive metabolites discriminated between RA patients classified as anti-TNF responders (R, n = 74) and non-responders (NR, n = 28). Among these, the anti-inflammatory oxylipin maresin 2 was higher in R while the pro-inflammatory oxylipins 15d PGJ2 and 5,6-diHETE were higher in NR. Twenty different metabolites discriminated anti-IL6 R (n=73) and NR (n=41) as shown in Figure 1. The anti-inflammatory oxylipin 14-15EET was higher in R while the pro-inflammatory oxylipins 16-HETE and 5S-HpETE were higher in NR. Figure 1. Volcano plots visualizing baseline metabolites associated with responders vs. non responders in a) anti-TNF and b) anti IL-6 therapy groups. Results are derived from multivariate logistic regression analysis of baseline metabolites and response to treatment categorized by MCID. Data plotted as the metabolite against its statistical significance, respectively reported as odds ratio (OR) and -log10(pvalue). Conclusion Circulating bioactive lipid analysis using LC/MS provided a rapid analysis of a wide range of metabolites and can be used to describe metabolic signatures that predict response to therapies. These results lay the groundwork for more deliberate investigations novel metabolic-based interventions to predict response to therapy and reduce arthritis morbidity. References [1]Pappas DA, Kremer JM, Reed G, Greenberg JD, Curtis JR. Design characteristics of the CORRONA CERTAIN study: a comparative effectiveness study of biologic agents for rheumatoid arthritis patients. BMC Musculoskeletal Disord 2014; 15: 113 [2]Curtis JR, Yang S, Chen L, Pope JE, Keystone EC, Haraoui B, Boire G, Thorne JC, Tin D, Hitchon CA, Bingham CO 3rd, Bykerk VP. Determining the Minimally Important Difference in the Clinical Disease Activity Index for Improvement and Worsening in Early Rheumatoid Arthritis Patients. Arthritis Care Res (Hoboken). 2015 Oct;67(10):1345-53. doi: 10.1002/acr.22606. PMID: 25988705; PMCID: PMC4580563. Disclosure of Interests Mona Alotaibi: None declared, Roxana Coras: None declared, Dimitrios A Pappas Speakers bureau: Sanofi, Novartis, Paid instructor for: Novartis, Consultant of: Roche, Sanofi, Joel M Kremer Speakers bureau: Pfizer, Consultant of: BMS, Geoffrey Thiele: None declared, Ted Mikuls Consultant of: Pfizer, Gilead, BMS, Sanofi, Mohit Jain Employee of: Sapient Bio, Monica Guma Grant/research support from: Pfizer, Novartis.